Videos are often changed from an original video stream to a modified one. The impetus to change is often related to the bandwidth of the target medium over which the modified video stream will be transmitted, but there are a variety of reason to modify videos. Other reasons for processing video include editing, compression and decompression, reformatting, video insertion and overlay, minimization of transmission errors, and modifying color for different displays, for example.
The video industry imposes limits on color reproduction in the modified video. In other words, the industry establishes standards to which the resultant video must pass to be acceptable. One problem that regularly appears is a color shift from the original to the modified video. Color shift is common in most video processing and difficult to empirically assess because determination of color is physiologically based and therefore necessarily subjective.
Previous methods for detecting such problematic changes in color have either required a) direct viewing of before and after videos, which is time consuming and sometimes both before and after video sources are not simultaneously available for viewing; b) use of vectorscopes or “color” which require trained personnel to interpret, and even then one may be misled because of lack of human vision model, i.e. the brightness of colors is missing so blacks often show up as bright colors on the vectorscope; c) “color” (UV of YUV or RGB based) peak-signal to noise ratio (PSNR) measurement, which can be automated, but also suffers from the issue of lack of human vision model aspects as does the vectorscope solution; d) human vision model type video quality analysis products such as the TEKTRONIX PQA300 quality analyzer can determine if perceptible chance in color has taken place, but it lacks many of the important adaptation mechanisms required to accurately predict how the color is different and, in some cases for particular viewing conditions, even if the color appears different; or e) using more advanced human vision model technology such as a Moving Image Color Appearance Model (MICAM), described in a U.S. Pat. No. 8,355,567 B2, filed on Dec. 10, 2009 entitled METHOD AND APPARATUS FOR IMPLEMENTING MOVING IMAGE COLOR APPEARANCE MODEL FOR VIDEO QUALITY RATINGS PREDICTION, and incorporated by reference herein. The output of the MICAM, however, may be difficult to interpret for an untrained operator and some distinctions in modified video may be difficult even for experts to appreciate.
Embodiments of the invention address these and other limitations in the prior art.